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Aussie research uses space tech to diagnose eye disease

16/05/2018By Matthew Woodley • Staff Journalist
Pattern recognition techniques used to assess satellite images could soon be employed to diagnose blinding eye diseases more effectively, thanks to research emanating out of the Centre for Eye Health (CEH).

The new approach combines the results of multiple ocular imaging techniques, and according to the study’s lead author Ms Angelica Ly, it can identify features of macular degeneration with a very high rate of success.


“We need an easier way of processing all the information to ensure that key signs don’t get missed. We have shown that our method is able to successfully classify a series of eyes with intermediate age-related macular degeneration 91% cent of the time.”
Angelica Ly, Centre for Eye Health

“The amount of diagnostic imaging information routinely available to clinicians has increased substantially over the past decade and this has created a form of ‘information overload’,” Ly said.

“We need an easier way of processing all the information to ensure that key signs don’t get missed. We have shown that our method is able to successfully classify a series of eyes with intermediate age-related macular degeneration 91% cent of the time.”

CEH estimates as many as 25% of patients with early or moderate age-related macular degeneration (AMD) disease remain undiagnosed in Australia, which it has described as a “major concern”. CEH director Professor Michael Kalloniatis said he first conceived of the idea of an automated approach to diagnosis 14 years ago but didn’t have the data to further explore its application.

“We could only test the hypothesis once these imaging techniques became more established,” Kalloniatis said.

“One of the other major challenges with age-related macular degeneration is to monitor patients so that those who may progress to the late stage are identified early. Progression is usually monitored through inspection of ocular imaging, but the current method is tedious and the accuracy is variable. Our study provides preliminary evidence that this monitoring can be done via a pattern recognition approach.”

It’s believed such an approach could have important applications for ocular imaging centres or for custom software incorporated by ophthalmic imaging manufacturers. As such, CEH hopes that commercialisation of the technique could see it routinely applied in AMD screening and monitoring processes, resulting in potentially better outcomes.

The study was published in Investigative Ophthalmology & Visual Science, while a provisional patent for the new technique has also been filed.

More information: The full study.

Image courtesy: Flickr | EUMETSAT



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